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Conference on New Media Studies (CoNMedia)

作者： Rosalina Genta Sahuri Hasanul Fahmi Joe Wesley Moerland Rila Mandala Informatics Study Program President University Indonesia Information System Study Program President University Indonesia Magister of Informatics Study Program President University Indonesia Faculty of Computing President University Indonesia

In Indonesia, mental health awareness is not as prominent as physical health, and many adolescents have experienced mental health problems. Some people hide their mental and emotional problems by appearing cheerful and peaceful, but research shows that body language and voice tone can reveal a person's inner psychological state. Similarly, handwriting can be analyzed through graphology to reveal personality traits such as honesty, emotional stability, and fears. Graphology is a time-consuming and expensive process, using image processing and machine learning, graphology can be done quickly without human bias. This research aims to predict the personality traits by implement image processing combined with machine learning to analyze handwriting features. Using lazy learner algorithm of K-Nearest Neighbor algorithm, SVM and Naïve Bayes, the application can predict the MBTI personality from handwriting image with an accuracy of 94%, 78%, and 93% respectively. From the experiment, it is shown that the application able to do the analysis of one's handwriting and then predict the personality traits, fully automated using a computer

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Watermelons Talk: Predicting Ripeness through Tapping

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IEEE Internet of Things Magazine 2024年第4期7卷 154-161页

作者： Lin, Yun-Wei Lin, Yi-Bing Chen, Wen-Liang Chang, Chia-Hui Li, Han-Kuan College of Artificial Intelligence Yang Ming Chiao Tung University (NYCU) NYCU China Medical University Miin Wu School of Computing National Cheng Kung University Research Center for Information Technology Innovation Academia Sinica College of Biological Science and Technology NYCU Industrial Development Graduate Program of College of Biological Science and Technology

During the commercial production of watermelons, farmers must swiftly assess fruit ripeness post-harvest to minimize losses through sorting based on edibility time. This process enhances marketability and productivity but is often very tedious in traditional approaches. This article delves into the multifaceted realm of Internet of Things (IoT) based real-time watermelon ripeness evaluation. Watermelons, subject to diverse degrees of ripeness, significantly impact the fruit's taste and texture. Notably, watermelons cease to mature after detachment from the vine, underscoring the importance of selecting the ripest specimens at purchase. Prompt post-harvest fruit ripeness assessment is pivotal to mitigate losses, ensuring accurate sorting based on edibility timeline. Consequently, diligent watermelon ripeness assessment by farmers gains importance for enhanced marketability and productivity. While manual techniques like tapping, color examination, and day counting serve practical purposes, their accuracy relies on subjective judgment. Currently, the prevailing method for assessing watermelon ripeness is the sound test. This tapping technique surprisingly rests on logical grounds, as the resulting sounds offer an adequate ripeness indicator. However, personal interpretations of these sounds are influenced by subjective experiences and traditional wisdom. This article investigates non-destructive methodologies for evaluating watermelon ripeness. Then we propose WatermelonTalk, an IoT based real-time deep learning platform designed for acoustic watermelon testing. We also introduce the concept of the 'tapping ensemble,' not previously found in the literature, which significantly enhances prediction accuracy. The article's contributions encompass the most comprehensive categorization of watermelons in the literature, specifically categorizing 1698 watermelons across 343 varieties by ripeness. Previous studies have considered either the 2-level test (unripe and ripe) or th

关键词： Productivity Deep learning Accuracy Real-time systems Acoustics Crops Farming Agricultural products Commercialization Color Testing

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Enhancing the Performance of E-Mode AlGaN/GaN HEMTs With Recessed Gates Through Low-Damage Neutral Beam Etching and Post-Metallization Annealing

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 150-155页

作者： Chen, Yi-Ho Ohori, Daisuke Aslam, Muhammad Lee, Yao-Jen Li, Yiming Samukawa, Seiji National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Graduate Degree Program of College of Electrical and Computer Engineering Hsinchu300093 Taiwan Tohoku University Institute of Fluid Science Sendai980-8577 Japan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Pioneer Semiconductor Innovation Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Institute of Communications Engineering Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan

This study investigated the electrical properties of AlGaN/GaN high-electron-mobility transistors (HEMTs) with varied recess depths under the gate electrode. We demonstrated a recess depth of approximately 6 nm, which was achieved through neutral beam etching (NBE) technique with a low etch rate of 1.8 nm/min, resulting in device enhancement-mode (E-mode) behavior with threshold voltage (Vth) of 0.49 V. The effects of post-metallization annealing (PMA) on the device performance were also examined. The results revealed that PMA treatment improves the DC characteristics of the devices, including maximum drain current (IDMAX), transconductance (gm), subthreshold swing (SS), on-off ratio, and off-state leakage current, with maximum enhancement percentage of 18.3% for IDMAX, 3758% for on-off ratio, and 54.3% for SS. Moreover, this study compared the recess depths of metal-insulator-semiconductor high-electron-mobility transistors (MIS-HEMTs) with the SiN dielectric layer. The results showed that MIS-HEMTs exhibit more negative Vth values, which can be attributed to the controlled surface states achieved through passivation. © 2020 IEEE.

关键词： Etching

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MULTISTYLE: Characterizing Multiplayer Cooperative Gameplay by Incorporating Distinct Player Playstyles in a Multi-Agent Planner 19

MULTISTYLE: Characterizing Multiplayer Cooperative Gameplay ...

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19th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2023

作者： Lang, Eric W. Young, R. Michael School of Computing University of Utah 201 Presidents’ Circle Salt Lake CityUT84112 United States Entertainment Arts and Engineering Program University of Utah 201 Presidents’ Circle Salt Lake CityUT84112 United States

ISBN: (纸本)157735883X

This paper presents MULTISTYLE, a multi-agent centralized heuristic search planner that incorporates distinct agent playstyles to generate solution plans where characters express individual preferences while cooperating to reach a goal. We include algorithmic details, an example domain, and multiple different solution plans generated with unique agent playstyle sets. We discuss our intent to incorporate this planner in a tool for game level designers to help them anticipate and understand how teams of players with distinct playstyles may play through their levels. Ultimately, MULTISTYLE generates solution plans with a novel and increased expressive range by attempting to satisfy sets of action and proposition preferences for each agent. Copyright © 2023, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

关键词： Multi agent systems

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A massively parallel speciation-based differential evolution algorithm applied to the 3D-AB protein structure prediction

A massively parallel speciation-based differential evolution...

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作者： Stubs Parpinelli, Rafael Boiani, Mateus Dias, André E. P. Graduate Program in Applied Computing State University of Santa Catarina Santa Catarina Joinville Brazil Rio Grande do Sul Porto Alegre Brazil Computer Science Department State University of Santa Catarina Santa Catarina Joinville Brazil

One of the most challenging problems in Bioinformatics is the finding of a protein conformation and it is known as the Protein Structure Prediction (PSP) problem. The main feature present in the AB off-lattice model is the use of polarity as the main driving force to guide the optimization process. The present work proposes an adaptive evolutionary algorithm based on GPU that is applied to the 3D-AB off-lattice PSP problem. The proposed approach is named cuDSMjDE, and is composed of a Dynamic Speciation-based Mutation Strategies Differential Evolution that employs the jDE mechanism to control F and CR parameters. A crowding strategy is also adopted, increasing competition between individuals and maintaining the diversity of solutions. All routines of the proposed algorithm are developed to run in GPU. During the experiments, eight Protein Data Bank sequences are employed. Results obtained concerning potential energy are competitive when compared with state-of-the-art algorithms. The use of a massively parallel architecture promoted the necessary scalability with speedups up to 708.78 (Figure presented.). © 2021 John Wiley & Sons, Ltd.

关键词： Evolutionary algorithms

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Automating Adjudication of Cardiovascular Events Using Large Language Models

arXiv

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arXiv 2025年

作者： Sivarajkumar, Sonish Ameri, Kimia Li, Chuqin Wang, Yanshan Jiang, Min Advanced Analytics and Data Sciences Eli Lilly and Company United States Intelligent Systems Program School of Computing and Information University of Pittsburgh United States

Cardiovascular events, such as heart attacks and strokes, remain a leading cause of mortality globally, necessitating meticulous monitoring and adjudication in clinical trials. This process, traditionally performed manually by clinical experts, is time-consuming, resource-intensive, and prone to inter-reviewer variability, potentially introducing bias and hindering trial progress. This study addresses these critical limitations by presenting a novel framework for automating the adjudication of cardiovascular events in clinical trials using Large Language Models (LLMs). We developed a two-stage approach: first, employing an LLM-based pipeline for event information extraction from unstructured clinical data and second, using an LLM-based adjudication process guided by a Tree of Thoughts approach and clinical endpoint committee (CEC) guidelines. Using cardiovascular event-specific clinical trial data, the framework achieved an F1-score of 0.82 for event extraction and an accuracy of 0.68 for adjudication. Furthermore, we introduce the CLEART score, a novel, automated metric specifically designed for evaluating the quality of AI-generated clinical reasoning in adjudicating cardiovascular events. This approach demonstrates significant potential for substantially reducing adjudication time and costs while maintaining high-quality, consistent, and auditable outcomes in clinical trials. The reduced variability and enhanced standardization also allows for faster identification and mitigation of risks associated with cardiovascular therapies. Copyright © 2025, The Authors. All rights reserved.

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Classification Based on Texture Analysis for Synthetic Hazy Image from Mount Kelud Haze Image Density 8

Classification Based on Texture Analysis for Synthetic Hazy ...

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8th International Conference on Electrical, Electronics and Information Engineering, ICEEIE 2023

作者： Nugroho, Fresy Basid, Puspa Miladin Safitri A. Arif, Yunifa Miftachul Diah, Norizan Mat Bahtiar, Firma Sahrul Nurhayati, Hani Kurniawan, Fachrul Priandani, Nurizal Dwi Dermawan, Dodik Arwin Universitas Islam Negeri Maulana Malik Ibrahim Informatics Engineering Faculty of Science and Technology Malang Indonesia School of Computing Sciences College of Computing Informatics and Media Universiti Teknologi Mara Shah Alam Malaysia Library and Information Science Universitas Islam Negeri Maulana Malik Ibrahim Faculty of Science and Technology Malang Indonesia Manajemen Informatika Program Vokasi Universitas Negeri Surabaya Surabaya Indonesia

ISBN: (纸本)9798350340501

This paper classifies the simulations of homogeneous synthetic images, heterogeneous synthetic hazy images, and original hazy images taken from CCTV (Close Circuit Television) of Mt. Kelud crater using the GLCM (Gray Level Co-Occurrence Matrix) method. The average feature values obtained using the GLCM (Gray Level Co-Occurrence Matrix) method are used to compare the similarity of gray feature values of the three and then classify thin, medium, and thick images. The results for classifying thin haze, medium haze, and thick haze on the homogeneous synthetic hazy image test data obtained an accuracy value of 50%, a precision value of 46%, and a sensitivity value of 65%. As for the classification of thin, medium, and thick fog on heterogeneous synthetic hazy images, test data obtained an accuracy value of 42%, a precision value of 32%, and a sensitivity value of 48%. © 2023 IEEE.

关键词： Textures

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Evaluating Reader Comprehension of Plan-Based Stories Containing Failed Actions 18

Evaluating Reader Comprehension of Plan-Based Stories Contai...

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18th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2022

作者： Sanghrajka, Rushit Young, R. Michael School of Computing University of Utah Salt Lake CityUT United States Entertainment Arts and Engineering Program University of Utah Salt Lake CityUT United States

ISBN: (纸本)1577358775

A growing number of algorithms for story planning include the ability to create stories with failed actions – in particular failed actions that occur because of the mistaken beliefs of the characters attempting them. To date, most of these systems have been evaluated analytically, primarily by comparing their expressive range to prior story generation systems. Empirical evaluation of these systems has been preliminary. In this paper, we outline a general comprehension-based approach to the evaluation of plan-based story generation. We describe how we specialize it for use evaluating story plans containing failed actions, and we describe the design and results of an experiment using this approach to evaluate plot lines produced by HEADSPACE, a system that models the beliefs of characters and uses that model to generate plot lines containing actions that are attempted but that fail. Copyright © 2022, Association for the Advancement of Artificial Intelligence (***). All rights reserved.

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Electrical Characteristic and Power Fluctuations of GAA Si NS CFETs by Simultaneously Considering Six Process Variation Factors

IEEE Open Journal of Nanotechnology

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IEEE Open Journal of Nanotechnology 2023年 4卷 229-238页

作者： Kola, Sekhar Reddy Li, Yiming National Yang Ming Chiao Tung University Parallel and Scientific Computing Laboratory Electrical Engineering and Computer Science International Graduate Program Hsinchu300093 Taiwan Parallel and Scientific Computing Laboratory National Yang Ming Chiao Tung University Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Communications Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Institute of Biomedical Engineering Hsinchu300093 Taiwan National Yang Ming Chiao Tung University Department of Electronics and Electrical Engineering Hsinchu300093 Taiwan

Characteristic variability induced by process variation effect (PVE) is one of technological challenges in semiconductor industry. In this work, we computationally study electrical characteristic and power fluctuations induced by six factors of PVE of the gate-all-around (GAA) silicon (Si) nanosheet (NS) complementary field-effect-transistors (CFETs) which are formed by vertically stacking n-FET on top of p-FET. Among the six factors, NS thickness (TNS), NS width (WNS), and gate length (LG) are identified as crucial factors contributing to large variations in device characteristics. The p-FET exhibits substantial off-state current fluctuation (about 151%) due to the bottom parasitic channel leakages. Compared with the magnitudes of dynamic and short circuit powers, the static power is marginal, but it possesses the largest fluctuation (up to 148%). If we assume that each factor of PVE has the same probability distribution as the others and all are mutually independent, the statistical sum of their power fluctuations will exhibit more than 50% overestimations, compared with the results when all factors are considered simultaneously. © 2020 IEEE.

关键词： III-V semiconductors

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An Efficient Hardware Design for the VVC Prediction Refinement with Optical Flow

IEEE Design and Test

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IEEE Design and Test 2025年

作者： Perleberg, Murilo Munoz, Marcello Maass, Denis Afonso, Vladimir Agostini, Luciano Porto, Marcelo Federal University of Pelotas Video Technology Research Group - Graduate Program in Computing Pelotas Brazil Video Technology Research Group - Sul-rio-grandense Federal Institute Pelotas Brazil

The Prediction Refinement with Optical Flow (PROF) is incorporated in the Affine Prediction of the Versatile Video Coding (VVC) standard. While the Affine Prediction allows the representation of complex motions in the scene, the PROF enhances video encoding efficiency by generating a virtual rotation on each subblock of the current block. Due to the intensive computational processing, this work presents a dedicated hardware design for the PROF and its integration with the Affine Motion Estimation Reconstructor. The synthesis results show that the proposed PROF Core design can process 120 frames per second of 4K Ultra-High-Definition resolution videos while dissipating 2.2mW. © 2013 IEEE.

关键词： Image coding

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